Redirected Walking (RDW) enables users to explore expansive virtual environments within limited physical spaces by subtly manipulating the mapping between their physical and virtual movements. One such manipulation, translation gain, alters the scale of user’s virtual forward movement relative to their physical forward movement. The primary objective of the presented study (n = 35) was to understand how changing the user’s translation gain in a constant manner affects their ability to detect the manipulation. Specifically, the study presented users with three different rates of change (slow, moderate, and fast), as well as two directions (increasing and decreasing) for the applied translation gain. The study was conducted using a “Method of Limits” psychometric technique, which allows for much quicker collection of the user’s detection threshold when compared to other psychometric techniques used in prior RDW literature. Our results show that both rate of change and direction had a significant effect on the participants’ detection thresholds, but also suggest that time of exposure to noticeable translation gain manipulations may have an impact on detection thresholds as well. Finally, we discuss these findings, their potential implications, and relevant future work.

Collaborative virtual environments afford new capabilities in telepresence applications, allowing participants to co-inhabit an environment to interact while being embodied via avatars. However, shared content within these environments often takes away the attention of collaborators from observing the non-verbal cues conveyed by their peers, resulting in less effective communication. Exaggerated gestures, abstract visuals, as well as a combination of the two, have the potential to improve the effectiveness of communication within these environments in comparison to familiar, natural non-verbal visualizations. We designed and conducted a user study where we evaluated the impact of these different non-verbal visualizations on users' identification time, understanding, and perception. We found that exaggerated gestures generally perform better than non-exaggerated gestures, abstract visuals are an effective means to convey intentional reactions, and the combination of gestures with abstract visuals provides some benefits compared to their standalone counterparts.

Virtual reality interactions that require a specific relationship between the virtual and physical coordinate systems, such as passive haptic interactions, are not possible with locomotion techniques using redirected walking. To address this limitation, recent research has introduced environmental alignment, which is the notion of using redirected walking techniques to align the virtual and physical coordinate systems such that these interactions are possible. However, the previous research has only implemented environmental alignment in a reactive manner, and the authors posited that better results could be achieved if a predictive algorithm was instead used. In this work, we introduce a novel way to model the environmental alignment problem as a version of the inverse kinematics problem which can be incorporated into several existing predictive algorithms, as well as a simple proof-of-concept implementation. An exploratory human subject study (N=17) was conducted to evaluate this implementation’s usability as a tool for authoring planned path redirected walking scenarios that incorporate physical interactivity. To our knowledge, this is the first study to evaluate redirected walking experience design tools and provides a possible framework for future studies. Our qualitative analysis of the results generated both guidance for integrating automatic solvers and broad recommendations for designing redirected path authoring tools.

Redirected walking can effectively utilize a user’s physical space when traversing larger virtual environments by using virtual self-motion gains for a user’s physical motions. In particular, curvature gain presents unique advantages in redirection but can lead to suboptimal orientations. To prevent this and add additional utility in redirected walking, we formally present strafing gain. Strafing gain seeks to add incremental lateral movements to a user’s position causing the user to walk along a diagonal trajectory while maintaining the original orientation of the user. In a study with 27 participants, we tested 11 values to determine the detection thresholds of strafing gain. The study, which was modeled on prior detection threshold studies, found that strafing gain could successfully redirect participants to walk along a 5.57° diagonal to the right and a 4.68° diagonal to the left. Furthermore, a supplementary study with 10 participants was conducted, verifying that orientation was maintained throughout redirection and validating the obtained detection thresholds. We discuss the implications of these findings and potential ways of improving these quantities in real-world applications.

Developing effective strategies for redirected walking requires extensive evaluations across a variety of factors that influence performance. Because these large-scale experiments are often not practical with user studies, researchers have instead utilized simulations to systematically test different algorithm parameters, physical space configurations, and virtual walking paths. Although simulation offers an efficient way to evaluate redirected walking algorithms, it remains an open question whether this evaluation methodology is ecologically valid. In this paper, we investigate the interaction between locomotion behavior and redirection gains at a micro-level (across small path segments) and macro-level (across an entire experience). This examination involves analyzing data from real users and comparing algorithm performance metrics with a simulated user model. The results identify specific properties of user locomotion behavior that influence the application of redirected walking gains and resets. Overall, we found that the simulation provided a conservative estimate of the average performance with real users and observed that performance trends when comparing two redirected walking algorithms were preserved. In general, these results indicate that simulation is an empirically valid evaluation methodology for redirected walking algorithms.

Interactions with the physical environment, such as passive haptic feedback, have been previously shown to provide richer and more immersive virtual reality experiences. A strict correspondence between the virtual and real world coordinate systems is a staple requirement for physical interaction. However, many of the commonly employed VR locomotion techniques allow for, or even require, this relationship to change as the experience progresses. The outcome is that experience designers frequently have to choose between flexible locomotion or physical interactivity, as the two are often mutually exclusive. To address this limitation, this paper introduces reactive environmental alignment, a novel framework that leverages redirected walking techniques to achieve a desired configuration of the virtual and real world coordinate systems. This approach can transition the system from a misaligned state to an aligned state, thereby enabling the user to interact with physical proxy objects or passive haptic surfaces. Simulation-based experiments demonstrate the effectiveness of reactive alignment and provide insight into the mechanics and potential applications of the proposed algorithm. In the future, reactive environmental alignment can enhance the interactivity of virtual reality systems and inform new research vectors that combine redirected walking and passive haptics.

Redirected walking enables users to locomote naturally within a virtual environment that is larger than the available physical space. These systems depend on steering algorithms that continuously redirect users within limited real world boundaries. While a majority of the most recent research has focused on predictive algorithms, it is often necessary to utilize reactive approaches when the user's path is unconstrained. Unfortunately, previously proposed reactive algorithms assume a completely empty space with convex boundaries and perform poorly in complex real world spaces containing obstacles. To overcome this limitation, we present Push/Pull Reactive (P2R), a novel algorithm that uses an artificial potential function to steer users away from potential collisions. We also introduce three new reset strategies and conducted an experiment to evaluate which one performs best when used with P2R. Simulation results demonstrate that the proposed approach outperforms the previous state-of-the-art reactive algorithm in non-convex spaces with and without interior obstacles.

Redirected walking has been shown to be an effective technique for allowing natural locomotion in a virtual environment that is larger than the physical environment. In this position paper, I identify two large limitations of redirected walking and provide brief descriptions of solutions. I continue to introduce the conceptual design for an algorithm, inspired by techniques in the field of coordinated multi-robotics, that improves upon the current state of redirected walking by addressing these limitations. I then explain how it will become the foundation for my thesis and provide future research vectors.

Redirected walking enables the exploration of large virtual environments while requiring only a finite amount of physical space. Unfortunately, in living room sized tracked areas the effectiveness of common redirection algorithms such as Steer-to-Center is very limited. A potential solution is to increase redirection effectiveness by applying two types of perceptual manipulations (curvature and translation gains) simultaneously. This paper investigates how such combination may affect detection thresholds for curvature gain. To this end we analyze the estimation methodology and discuss selection process for a suitable estimation method. We then compare curvature detection thresholds obtained under different levels of translation gain using two different estimation methods: method of constant stimuli and Green's maximum likelihood procedure. The data from both experiments shows no evidence that curvature gain detection thresholds were affected by the presence of translation gain (with test levels spanning previously estimated interval of undetectable translation gain levels). This suggests that in practice currently used levels of translation and curvature gains can be safely applied simultaneously. Furthermore, we present some evidence that curvature detection thresholds may be lower that previously reported. Our estimates indicate that users can be redirected on a circular arc with radius of either 11.6m or 6.4m depending on the estimation method vs. the previously reported value of 22m. These results highlight that the detection threshold estimates vary significantly with the estimation method and suggest the need for further studies to define efficient and reliable estimation methodology.

Consumer adoption of virtual reality technology has historically been held back by poor accessibility, the lack of intuitive multi-user capabilities, dependence on external infrastructure for rendering and tracking, and the amount of time and effort required to enter virtual reality systems. This poster presents the current status of our work creating MuVR, a Multi-User Virtual Reality platform that seeks to overcome these hindrances. The MuVR project comprises four main goals: scalable and easy to use multi-user capabilities, portable and self-contained hardware, a rapidly deployable system, and ready accessibility to others. We provide a description of the platform we developed to address these goals and discuss potential directions for future work.